An image segmentation based on a genetic algorithm for determining soil coverage by crop residues

Ribeiro Seijas, Ángela and Ranz, Juan and Burgos Artizzu, Xavier and Pajares, Gonzalo and Sanchez del Arco, Maria J. and Navarrete, Luis (2011). An image segmentation based on a genetic algorithm for determining soil coverage by crop residues. "Sensors", v. 11 (n. 6); pp. 6480-6492. ISSN 14248220. https://doi.org/10.3390/s110606480.

Description

Title: An image segmentation based on a genetic algorithm for determining soil coverage by crop residues
Author/s:
  • Ribeiro Seijas, Ángela
  • Ranz, Juan
  • Burgos Artizzu, Xavier
  • Pajares, Gonzalo
  • Sanchez del Arco, Maria J.
  • Navarrete, Luis
Item Type: Article
Título de Revista/Publicación: Sensors
Date: 2011
ISSN: 14248220
Volume: 11
Subjects:
Faculty: Otros Centros UPM
Department: Otro
Creative Commons Licenses: Recognition - No derivative works - Non commercial

Full text

[img]
Preview
PDF - Requires a PDF viewer, such as GSview, Xpdf or Adobe Acrobat Reader
Download (736kB) | Preview

Abstract

Determination of the soil coverage by crop residues after ploughing is a fundamental element of Conservation Agriculture. This paper presents the application of genetic algorithms employed during the fine tuning of the segmentation process of a digital image with the aim of automatically quantifying the residue coverage. In other words, the objective is to achieve a segmentation that would permit the discrimination of the texture of the residue so that the output of the segmentation process is a binary image in which residue zones are isolated from the rest. The RGB images used come from a sample of images in which sections of terrain were photographed with a conventional camera positioned in zenith orientation atop a tripod. The images were taken outdoors under uncontrolled lighting conditions. Up to 92% similarity was achieved between the images obtained by the segmentation process proposed in this paper and the templates made by an elaborate manual tracing process. In addition to the proposed segmentation procedure and the fine tuning procedure that was developed, a global quantification of the soil coverage by residues for the sampled area was achieved that differed by only 0.85% from the quantification obtained using template images. Moreover, the proposed method does not depend on the type of residue present in the image. The study was conducted at the experimental farm “El Encín” in Alcalá de Henares (Madrid, Spain).

More information

Item ID: 13716
DC Identifier: http://oa.upm.es/13716/
OAI Identifier: oai:oa.upm.es:13716
DOI: 10.3390/s110606480
Official URL: http://www.mdpi.com/1424-8220/11/6/6480
Deposited by: Memoria Investigacion
Deposited on: 15 Nov 2012 12:54
Last Modified: 24 Feb 2017 17:53
  • Logo InvestigaM (UPM)
  • Logo GEOUP4
  • Logo Open Access
  • Open Access
  • Logo Sherpa/Romeo
    Check whether the anglo-saxon journal in which you have published an article allows you to also publish it under open access.
  • Logo Dulcinea
    Check whether the spanish journal in which you have published an article allows you to also publish it under open access.
  • Logo de Recolecta
  • Logo del Observatorio I+D+i UPM
  • Logo de OpenCourseWare UPM